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Related Concept Videos

Heart Failure VI: Adjunct Therapies01:22

Heart Failure VI: Adjunct Therapies

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Additional therapies for treating patients with heart failure (HF) may include procedural interventions, supplemental oxygen, the management of sleep disorders, and nutritional therapy.Procedural InterventionsImplantable Cardioverter-Defibrillator: For patients at risk of life-threatening arrhythmias due to severe left ventricular dysfunction, an Implantable Cardioverter-Defibrillator (ICD) can detect and terminate these arrhythmias, preventing sudden cardiac death and improving survival rates.
69
Heart Failure V: Medical Management01:30

Heart Failure V: Medical Management

64
Medical Management of Acute Decompensated Heart Failure (ADHF)The primary goals of therapy for patients hospitalized with acute decompensated heart failure (ADHF) include:Relieving symptomsOptimizing volume statusSupporting oxygenation and ventilationMaintaining cardiac output (CO) and end-organ perfusionIdentifying and addressing the cause of ADHFPreventing complicationsProviding patient education on factors precipitating HF exacerbationPlanning for dischargeOngoing monitoring and assessment...
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Heart Failure II: Pathophysiology01:29

Heart Failure II: Pathophysiology

144
Systolic Heart Failure and Compensatory MechanismsSystolic heart failure (also termed HFrEF, Heart Failure with Reduced Ejection Fraction) is the most prevalent type of heart filure. It results in a decreased volume of blood being pumped from the ventricle. The aortic arch and carotid sinuses have baroreceptors that detect reduced blood pressure, triggering the sympathetic nervous system (SNS) to release epinephrine and norepinephrine. Initially, this response aims to boost heart rate and...
144
Heart Failure I: Introduction01:27

Heart Failure I: Introduction

183
Heart failure refers to a clinical syndrome caused by structural or functional cardiac disorders that prevent the heart from pumping an adequate amount of blood to meet the body's metabolic needs. This condition often arises from myocardial infarction or ischemia, leading to decreased cardiac output, reduced tissue perfusion, impaired gas exchange, fluid volume imbalance, and decreased functional ability.Heart failure can result from disruptions in the mechanisms that regulate cardiac output...
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Heart Failure Drugs: Inhibitors of Renin-Angiotensin System01:26

Heart Failure Drugs: Inhibitors of Renin-Angiotensin System

645
The activation of the sympathetic nervous system and the renin-angiotensin-aldosterone system (RAAS) contributes to cardiac remodeling, and inhibiting the RAAS is a pharmacological target in heart failure management. As a result, neurohumoral modulation is a crucial treatment principle for managing heart failure. This approach involves using medications like ACE inhibitors (ACEIs), angiotensin receptor blockers (ARBs), β-blockers, mineralocorticoid receptor antagonists (MRAs), and neutral...
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Heart Failure III: Clinical Manifestations01:26

Heart Failure III: Clinical Manifestations

119
Heart failure (HF) manifests primarily as dyspnea, fatigue, and fluid retention, resulting in peripheral and pulmonary edema. Symptoms may vary depending on which ventricle is more affected, left or right.Left-Sided Heart FailureAlso known as left ventricular failure, this condition results from the left ventricle's inability to fill or eject sufficient blood into the systemic circulation. It leads to pulmonary congestion, which occurs when the left ventricle fails to eject blood effectively...
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Related Experiment Video

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In Silico Clinical Trials for Cardiovascular Disease
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Multiomics, virtual reality and artificial intelligence in heart failure.

Patrick A Gladding1, Suzanne Loader1, Kevin Smith2

  • 1Department of Cardiology, Waitemata District Health Board, Auckland 0620, New Zealand.

Future Cardiology
|May 19, 2021
PubMed
Summary

Multiomics combined with machine learning, including advanced ECG (AECG) and echocardiography AI (Echo AI), shows promise for assessing heart failure with reduced ejection fraction (HFrEF). These AI tools demonstrated comparable accuracy to traditional biomarkers in diagnosing HFrEF.

Keywords:
artificial intelligencemetabolomicsmultiomicsvolatilomics

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Area of Science:

  • Cardiology
  • Biomarkers
  • Artificial Intelligence in Medicine

Background:

  • Heart failure with reduced ejection fraction (HFrEF) requires advanced diagnostic tools.
  • Multiomics approaches offer deeper biological insights than conventional methods.
  • Machine learning (ML) applied to physiological signals and imaging holds potential for improved HFrEF assessment.

Purpose of the Study:

  • To investigate the utility of multiomics, advanced ECG (AECG), and echocardiography AI (Echo AI) in patients with HFrEF.
  • To evaluate the diagnostic accuracy of ML-based AECG and Echo AI compared to established HFrEF biomarkers.
  • To explore the physiological responses to stress in HFrEF patients using these advanced techniques.

Main Methods:

  • Multiomic profiling (metabolomics, volatilomics) was performed on plasma and urine from 46 HFrEF patients and 20 controls.
  • AECG and Echo AI analyses were conducted, with a subset undergoing virtual reality mental stress testing.
  • HFrEF diagnosis was confirmed using left ventricular global longitudinal strain, ejection fraction (EF), and N-terminal prohormone BNP levels.

Main Results:

  • AECG demonstrated diagnostic accuracy comparable to N-terminal prohormone BNP for HFrEF (AUC=0.95).
  • Echo AI measurements showed strong correlations with standard echocardiographic parameters like LV volumes and LVEF.
  • Mental stress testing revealed arrhythmic biomarkers on AECG and blunted autonomic responsiveness in HFrEF patients.

Conclusions:

  • Multiomics integrated with ML, particularly AECG and Echo AI, presents a promising avenue for HFrEF assessment.
  • AI-driven analyses of ECG and echocardiography can provide valuable diagnostic and prognostic information.
  • These advanced techniques offer novel insights into the pathophysiology and stress response in HFrEF.